Instructions to use Superlore/clip-vit-large-patch14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Superlore/clip-vit-large-patch14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Superlore/clip-vit-large-patch14") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("Superlore/clip-vit-large-patch14") model = AutoModelForZeroShotImageClassification.from_pretrained("Superlore/clip-vit-large-patch14") - Notebooks
- Google Colab
- Kaggle
Commit History
nits throw on bad request 426785e
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refactor inference request structure d318463
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change owner to superlore user account 7a7f986
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adds handler.py for custom inference d26a895
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initial commit - copy https://huggingface.co/openai/clip-vit-large-patch14 93cf9b4
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